The information contained herein is not meant to be exhaustive or present the best-in-class references in the field. Instead, it just contains a brief perspective on the topic. Surely, important aspects are neglected here, but that does not happen on purpose.

Automatic optimization is a field with much work still to be carried out on several fronts. Among them we have:

Optimization algorithms, in particular the choice of the most appropriate one for any given problem at hand;

Speed-up strategies for very expensive cases, like the Response Surface methodology, again something which can be very much case-dependent;

Ancillary steps, like Design-of-Experiments or Uncertainty Quantification (e.g., as required in Robust Design) for optimal usage of resources and real-life analysis of problems.

In the general context of CAE, optimization is simulation-time intensive, making its usage cost to be high, at times. However, this does not diminish its usefulness. So much so that there are already quite a few commercially available tools which have a fair amount of success:

blueCAPE has worked with modeFrontier in the past, and can therefore testify to the efficiency and effectiveness gains that Automatic Optimization can deliver.

However, there also very good tools available in the Open Source world. In particular, if you know your optimization problem well and have human resources skilled enough to work directly at source code level, you can do things in-house (or hire someone to do it for you). Some good sources of information:

openMDAO, which is an open-source Multidisciplinary Design Analysis and Optimization (MDAO), written in Python. It can be used to develop an integrated analysis and design environment in engineering problems.

blueFIRE is a robust computer program to simulate the propagation of wildlife fires. Due to its degree of interactivity and faster-than-real-time nature, it aims to be a helpful tool in forest-fire fighting.

Several physical and numerical models are available to choose from, allowing the user to adapt the program to his/her needs or to conform to best practices established with other modelling systems, like FARSITE. Also, the range of valid fuel models comprises several classification systems, including the one from the Northern Forest Fire Laboratory, USA.

It has the capacity to employ detailed meteorological fields (e.g., prognostic) in the forest-fire simulation, alongside variations in the fuel moisture content.

blueFIRE has been designed from the ground-up to be a flexible tool, that can either work as a standalone application or embedded in other, more encompassing, environments.

blueFIRE was developed in 2007 to be included in the SIGEL project developed by TECMIC - Tecnologias de Microelectrónica, S.A.
SIGEL stands for "Sistema Integrado para a Gestão de Situações de Emergência e Logística", which translates to "Integrated System for Management of Emergencies and Logistics", one of which such emergencies is forest fires. BlueFIRE handles the forest fire simulations in a seamless integrated manner in SIGEL.